Part 4

Calorimeter

At the conclusion of these experiments, the accuracy of our calorimetry apparatus was tested by burning an ethanol lamp in the metabolism chamber. During these tests a CO{2} analyzer was incorporated into the system (Beckman, LB-2). Results demonstrated that we measured 84% of the oxygen consumed by the lamp as well as 84% of the water and CO{2} it produced; standard deviation = ±2.6, ±5.0, and ±3.6, respectively (n = 27). Average respiratory quotient (RQ) calculated from these data was O.657 ±0.008 (n = 27), which is 99.5% of that predicted (0.66). McNab (1988b) reports that the accuracy of open-flow indirect calorimetry systems, such as ours, depends on the rate of air flow through the animal chamber. If flow rates are too low, there is inadequate mixing of air within the chamber, and the rate of oxygen consumption, as calculated from the difference in oxygen content of air flowing into and out of the chamber (Depocas and Hart, 1957), is underestimated. At some critical rate of air flow, which is unique to each combination of chamber and animal, this situation changes such that measured rates of oxygen consumption become independent of any further increase in flow rate (McNab, 1988b). In recent tests of our system, where we burned the ethanol lamp at a variety of chamber flow rates, the efficiency of measurement increased linearly as flow rate increased, and the critical rate of air flow was about 6.7 L/min. This appeared to explain why a flow rate of 3.0 L/min underestimated oxygen consumption of the ethanol lamp.

Our earlier tests of the efficiency of our system indicated that although we underestimated actual oxygen consumption of the ethanol lamp, we did so with a fair degree of precision; probably because flow rates were closely controlled. During our metabolic measurements, chamber flow rates also were closely controlled at 3.0 L/min, and we believe, therefore, that these measurements also were carried out with a high degree of precision. Consequently, all measured values of oxygen consumption and water production were considered to be 84% of their actual value and were adjusted to 100% before being included in this report.

Body Temperature Transmitters

The calibration of all temperature-sensitive radio transmitters drifted over time. Transmitters were calibrated before they were surgically implanted and again after they were removed from the animals. Although the drift of each transmitter was unique, it was also linear (S. Tomkiewicz, Telonics, Inc., pers. com.). All body temperature measurements were corrected from timed extrapolations of the difference between starting and ending calibrations.

STATISTICAL METHODS

Values of oxygen consumption, evaporative water loss, and body temperature were plotted as a function of chamber air temperature. Linear regressions of oxygen consumption at temperatures below the thermoneutral zone (T{n}), and evaporative water loss at temperatures above freezing, were determined with the SAS (1982) GLM procedure. Lower critical temperature (T{lc}) was determined graphically from intersection of the line representing [.H]{b} and the regression line representing oxygen consumption below T{n}. Slopes and intercepts of regression lines, as well as other mean values, were compared with t-tests (Statistical Analysis System, 1982; Ott, 1984:138-175). Unless indicated otherwise, data are expressed as mean ± standard deviation (s.d.).

ESTIMATING INTRINSIC RATE OF NATURAL INCREASE

We employed the method first described by Cole (1954) to calculate r_{max}:

1 = e^{-r{max}} + b·e^{-r{max}(a)} - b·e^{r_{max}(n+1)} Eq. 2

where a is potential age of females first producing young, b is potential annual birth rate of female young, and n is potential age of females producing their final young. After life-history data were substituted into Eq. 2, r_{max} was determined by trial and error substitution (Hennemann, 1983).

Because r{max} represents the genetically fixed, physiologically determined maximum possible rate of increase, data on earliest possible age of female reproduction, highest possible birth rate of female young, and longest possible female reproductive life span were used for a, b, and n, respectively. Calculated values, therefore, represent physiologically possible, not ecologically possible, intrinsic rates of increase (Hennemann, 1983, 1984; Hayssen, 1984; McNab, 1984b). Values of n were derived from longevity records for captive animals, and as these were all large values of similar duration (14-16 years), they had very little effect on r{max}. All species considered have one litter per year, and because their sex ratios at birth are about 50:50, variation in b was due to differences in litter size. Therefore, age of first reproduction and litter size had the greatest effect on r{max}. Intrinsic rate of increase scales to body mass (Fenchel, 1974), and we removed this effect by comparing each calculated r{max} with the value expected (r_{maxe}) on the basis of body mass (Hennemann, 1983).

COMPARISON OF ADAPTIVE UNITS

Dimensionless numbers for each of the four variables used in calculating composite scores were derived as follows. Ratios of measured to predicted values were used for basal metabolism (H{br}) and minimum wet thermal conductance (C{mwr}). Thermoregulatory ability at low temperatures is closely related to the ratio H{br}/C{mwr} (McNab, 1966). This ratio was used, therefore, to gauge each species' cold tolerance. For D{d} we used the ratio of food categories actually used by a species to the total number of food categories taken by all species tested (D{dr}). The ratio of calculated to expected intrinsic rates of natural increase was used to derive r_{maxr}. Composite scores were calculated as

Composite score = [(H{br}/C{mwr}) + D{dr} + r{maxr}]/3 Eq. 3

The correlation between number of climates these species occupy and their composite scores was tested by linear regression.

$Results$

BODY MASS

According to monthly live-trapping records, the body mass of free-ranging female raccoons increased from 3.6 ±0.6 kg during summer to 5.6 ±0.8 kg in early winter, and the mass of free-ranging males increased from 4.0 ±0.5 to 6.7 ±0.9 kg during the same interval. These seasonal changes in body mass were due to fluctuations in the amount of body fat and represent a mechanism for storing energy during fall for use in winter. In summer, captive and trapped male and captive female raccoons had the same body mass (4.73 ±0.61, 4.41 ±0.70, and 4.67 ±0.88 kg, respectively, Table 2). Mass of captive females did not change between seasons, whereas captive males were heavier in winter than summer (p<0.005; Table 2). This seasonal change in mass of our captive males was of a much smaller magnitude (0.6 kg) than that observed for wild males (2.7 kg). During winter, captive males (5.34 ±1.39 kg) were heavier than captive females (4.49 ±0.98 kg; p<0.005; Table 2). Thus, our captive animals maintained a body mass throughout the year that was intermediate to the range of values found for wild raccoons in the same area.

TABLE 2.--Body mass in kg and basal metabolism (mL O{2}·kg^{-0.75}·h^{-1}) of Procyon lotor_ in summer and winter (s.d. = standard deviation and n = number of observations).

----------------+----------------------------------------------------- Season and sex | Body mass, ±s.d., (n) Basal metabolism, ±s.d., (n) ----------------+----------------------------------------------------- Summer | Trapped male | 4.41 ±0.70 (52) 780 ±112 (20) Captive male | 4.73 ±0.61 (22) 680 ±102 (8) Captive female| 4.67 ±0.88 (41) 618 ± 92 (13) Winter | Captive male | 5.34 ±1.39 (31) 704 ± 81 (19) Captive female| 4.49 ±0.98 (42) 667 ±139 (25) ----------------+-----------------------------------------------------

BASAL METABOLIC RATE

Within thermoneutrality, [.H]{b} (mL O{2}·g^{-1}·h^{-1}) was 0.54 ±0.09 for trapped males in summer, 0.46 ±0.07 for captive males in summer, 0.42 ±0.07 for captive females in summer, 0.47 ±0.06 for captive males in winter, and 0.46 ±0.10 for captive females in winter (Figures 2, 3). Ratios of these measured values to those predicted by the Kleiber (1932, 1961:206) equation are 1.28, 1.12, 1.02, 1.17, and 1.09, respectively. To minimize the effect of body size (Mellen, 1963) and to facilitate comparisons between sexes and seasons and between captive and trapped animals, basal metabolism also was calculated as a function of metabolic body size (mL O_{2}·kg^{-0.75}·h^{-1}; Table 2). Based on this analysis, trapped summer males had a higher basal metabolism than captive males (p<0.025) or females (p<0.005) in either season (Table 2). There was no difference in basal metabolism between captive males and females in either summer or winter, and there was no seasonal difference in their basal metabolic rates (Table 2).

MINIMUM THERMAL CONDUCTANCE

Minimum wet and dry thermal conductances were calculated using Eqs. 4 and 5

C{mw} = [.H]{r} / (T{b} - T{a}) Eq. 4

C{md} = ([.H]{r} - [.E]{eq}) / (T{b} - T_{a}) Eq. 5

where C{mw} is wet and C{md} is dry conductance (mL O{2}·g^{-1}·h^{-1}·°C^{-1}); [.H]{r} is the lowest resting metabolic rate measured at each temperature (mL O{2}·g^{-1}·h^{-1}); [.E]{eq} is oxygen equivalent for heat lost by evaporation [[.E]{eq} = mL O{2}·g^{-1}·h^{-1} = [.E]·[lambda]/[gamma], where [.E] is evaporative water loss (mg·g^{-1}·h^{-1}), [lambda] is heat of vaporization for water (2.43 J/mg), and [gamma] is heat equivalent for oxygen (20.097 J/mL)]; T{b} is body temperature (°C); and T{a} is chamber air temperature (°C). Only data from animals equipped with temperature-sensitive radio transmitters were used for these calculations.